Count Me In Metastatic Breast Cancer Cohort: Genetic Variants and Time to Metastasis

63 female participants from the Count Me In Metastatic Breast Cancer Project were analyzed for associations between genetic variants and time to metastasis. The dataset includes whole-exome sequencing data from saliva samples linked to medical and self-reported patient data, with a mean time to metastasis of 732.6 days. The secondary analysis, authored by G. M. Gehling and updated in May 2026, identified CXCL12 and GAPDH as candidate genes.

Use Cases

• Identify genetic variants associated with metastatic timing based on whole-exome sequencing data.
• Validate candidate genes like CXCL12 and GAPDH in independent metastatic breast cancer cohorts.
• Build predictive models for time-to-metastasis using clinical and genomic features mentioned in the description.

Strengths

• Data is linked to medical and self-reported patient records from a specific cohort (Count Me In MBC Project).
• Analysis includes 63 participants with fully observed, right-skewed time-to-metastasis data (median 132 days).
• Findings were validated using sensitivity analyses with accelerated failure time Weibull models.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The sample size of 63 participants is small for genetic association studies.

Provenance

Source

Secondary analysis of the Count Me In: The Metastatic Breast Cancer Project (CMI-MBCProject), available through dbGaP (phs001709.v1.p1).

Collection Method

Retrospective analysis of cross-sectional genomic data linked to medical and self-reported patient data; whole-exome sequencing from saliva samples.

Freshness

Last updated 2026-05-29 06:21:29; freshness should be verified.